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NumPy v2.5 Manual - Home NumPy v2.5 Manual - Home
  • User Guide
  • API reference
  • Building from source
  • Development
  • Release notes
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  • User Guide
  • API reference
  • Building from source
  • Development
  • Release notes
  • Learn
  • NEPs
  • GitHub

Section Navigation

  • NumPy’s module structure
  • Array objects
  • Universal functions (ufunc)
  • Routines and objects by topic
    • Constants
    • Array creation routines
    • Array manipulation routines
      • numpy.copyto
      • numpy.ndim
      • numpy.shape
      • numpy.size
      • numpy.reshape
      • numpy.ravel
      • numpy.ndarray.flat
      • numpy.ndarray.flatten
      • numpy.moveaxis
      • numpy.rollaxis
      • numpy.swapaxes
      • numpy.ndarray.T
      • numpy.transpose
      • numpy.permute_dims
      • numpy.matrix_transpose
      • numpy.atleast_1d
      • numpy.atleast_2d
      • numpy.atleast_3d
      • numpy.broadcast
      • numpy.broadcast_to
      • numpy.broadcast_arrays
      • numpy.expand_dims
      • numpy.squeeze
      • numpy.asarray
      • numpy.asanyarray
      • numpy.asmatrix
      • numpy.asfortranarray
      • numpy.ascontiguousarray
      • numpy.asarray_chkfinite
      • numpy.require
      • numpy.concatenate
      • numpy.concat
      • numpy.stack
      • numpy.block
      • numpy.vstack
      • numpy.hstack
      • numpy.dstack
      • numpy.column_stack
      • numpy.split
      • numpy.array_split
      • numpy.dsplit
      • numpy.hsplit
      • numpy.vsplit
      • numpy.unstack
      • numpy.tile
      • numpy.repeat
      • numpy.delete
      • numpy.insert
      • numpy.append
      • numpy.resize
      • numpy.trim_zeros
      • numpy.unique
      • numpy.pad
      • numpy.flip
      • numpy.fliplr
      • numpy.flipud
      • numpy.roll
      • numpy.rot90
    • Bit-wise operations
    • String functionality
    • Datetime support functions
    • Data type routines
    • Mathematical functions with automatic domain
    • Floating point error handling
    • Exceptions and Warnings
    • Discrete Fourier Transform
    • Functional programming
    • Input and output
    • Indexing routines
    • Linear algebra
    • Logic functions
    • Masked array operations
    • Mathematical functions
    • Miscellaneous routines
    • Polynomials
    • Random sampling
    • Set routines
    • Sorting, searching, and counting
    • Statistics
    • Test support
    • Window functions
  • Typing (numpy.typing)
  • NumPy C-API
  • Array API standard compatibility
  • CPU/SIMD optimizations
  • Thread Safety
  • Global Configuration Options
  • NumPy security
  • Testing guidelines
  • Status of numpy.distutils and migration advice
  • NumPy and SWIG